Bibliographic record
Abstract
A merican Studies has historically dealt almost exclusively with the United States. This nation-centered approach is what “American Studies” as originally conceived in the 1930s and 1940s was all about, and it has remained the dominant approach to American Literature for a long time. Toward the end of the twentieth century, however, in the wake of globalizing tendencies not only in economics, politics, and technology, but also in the context of literature and culture and in the resulting “transnational turn,” American Studies has opened up to a transnational view of American literature and culture. Americanist scholars’ investigations have thus started to also reach beyond the borders of the United States and to examine the connection between American Literature and other literatures and cultures, or sometimes even to take a “postnational” approach to literature (i.e., contesting the conceptual validity of nation-states in a globalized world), thereby recognizing both the effects of complex migratory movements and the way national borders have suppressed Indigenous conceptions of what is now designated “North America.” Canadian Studies underwent a similar development, though with a time lag of a few decades (the establishment of Canadian Studies programs at universities in the 1970s, and transnational Canadian Literature Studies since the 1990s and particularly in the new millennium). 1 These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.006 | 0.002 |
| Scholarly communication | 0.008 | 0.003 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.322 | 0.107 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".